Výzkumná zpráva

Grim J., Somol P.

Research Report

2217

ÚTIA AV ČR

Praha

2008

Ing. Jiří Grim, CSc. (ÚTIA - Oddělení rozpoznávání obrazů)

Distribution mixtures, Screening Mammography, Local Statisti

We propose statistically based preprocessing of screening mammograms with the aim to emphasize suspicious areas. We estimate the local statistical texture model of a single mammogram in the form of multivariate Gaussian mixture. The probability density is estimated from the data obtained by pixelwise scanning of the mammogram with the search window. In the second phase, we evaluate the estimated density at each position of the window and display the corresponding log-likelihood value as a gray level at the window center. Light gray levels correspond to the typical parts of the image and the dark values reflect unusual places. The resulting log-likelihood image exactly correlates with the structural details of the original mammogram, emphasizes locations of similar properties by contour lines and may provide additional information to facilitate diagnostic interpretation.